Dalton J. Glove §

520-***-**** adlylx@r.postjobfree.com

https://github.com/SaltyDalty0

https://www.linkedin.com/in/dalton-glove

OBJECTIVE: Mathematics Undergraduate student seeking full-time position to apply technical knowledge and research skills in STEM related field. WORK EXPERIENCE:

BH PIRE EHT Project, Assist. Data Analyst Tucson, March 2019-present

• Data acquisition (SQL/MongoDB), visualization & prediction for ML (Python).

• Push data analysis to basic website (Docker/html/CSS/JS). Main Library ILL DDA, Student Worker Tucson, Oct 2018-present

• Filing and loaning research material between institutions, via Iliad/Alma software. ANALYSIS/COMPUTATIONAL SKILLS:

Technical: Dimensionality reduction, Time series correlation and prediction, Machine Learning, Statistical analysis, Network visualization and analysis, project applications of Topology, Classification and Clustering, Natural language processing, Web scraping and Proof logic. Software: Python, R, Matlab, Tableau, Gephi, Docker, Html, CSS, Latex, Mathematica. EDUCATION:

BS APPLIED MATH • MAY 2021 • UNIVERSITY OF ARIZONA

-Minors in Physics and Data Science & Statistics

Coursework: Algebraic Topology, Linear Algebra, Group Theory, Formal Reasoning, and Graphical Dif. Eq. Analysis, Bessel functions, Data Modeling.

-Statistics & Data Science: Statistical tests & Error analysis, Linear Regression and Monte Carlo

-Physics: Theoretical Mechanics, Basic QM, and Computational analysis in Python, Labs in E/M, Thermodynamics, Optics, & Chemistry.

BA PHILOSOPHY • MAY 2021 • UNIVERSITY OF ARIZONA

-Minor in Chinese Language

Coursework: Consciousness/Cognition, Phil. of Science, Existentialism, Symbolic Logic, Computer-Ethics, Formal Semantics, Evolutionary Moral Psychology, Language Psychology. PROJECTS/SUMMARY CV:

Network Analysis: Awaiting review of ICM/MCM contest project submission analyzing characteristics and influences between artists and their respective genres of music via directed network visualizations. Data analysis and 25 page project report done in four day period. Time series analysis: (cross/auto-) Correlation of weather sources and stock prices, identifying trends for Machine learning bot. Generate optimized stock portfolios with risk analysis and prediction methods, applying several methods for improvements in predictions, error and dimensionality reduction. Theoretical algebraic topology global trend analysis. Natural Language Processing: Web scrape Wikipedia articles and use NPL methods with dimensional reduction to cluster and classify into genres, access Twitter API for sentiment analysis. Pride & Prejudice like passage generator bot. Dimensionality Reduction: Topological analysis, Principal Component Analysis for classifying, correlating, and clustering of Iris pedal, stock price, financial, Wiki-page, Twitter post, and MNIST (hand-written numbers) datasets.